Implementation of the Network-Based Moving Sliding Mode Control Algorithm to the Rotary Inverted Pendulum System

Year 2019, Volume: 3 Issue: 1, 32 - 41, 23.05.2019

Muhammet Aydın Oğuz Yakut Hakan Tutumlu

Abstract

In
this study, the most preferred in control applications rotary inverted pendulum
system (rip)  is dealt. The coordinates
of the center of gravity of the rip elements were found and the total kinetic
and potential energies of the system were obtained. Lagrange function has been
formed by using kinetic and potential energy expressions. Expressions giving
the equations of motion of the system have been found by taking into
consideration the Lagrange method. Using the state variables, the pendulum
angle of the system has been controlled by the moving sliding mode control
method via the program written in Matlab. The slope of the sliding surface is
calculated by artificial neural networks. Optimum values of weight and bias
coefficients of artificial neural networks are found by using the genetic
algorithm. From the results, it has been seen that the pendulum angle reaches
to about 25 Nm motor torque and the reference value reaches about 3 seconds and
the error is about zero.

Keywords

Rotary inverted pendulum, Moving sliding mode control

References

• [1] Bugeja, M., “Non-Linear Swing-Up and Stabilizing Control of an Inverted Pendulum System”, EUROCON, Ljubljana, Slovenia (2003).
• [2] Stimac, A.K., “Standup and Stabilization of the Inverted Pendulum”, Massachusetts Institute of Technology, 1999.
• [3] Zhong, W., Röck, H., “Energy and passivity Based control of the double inverted pendulum on a cart”, IEEE Conference on Control Applications, 2001.
• [4] Krishen, J., Becerra, V.M., “Efficient Fuzzy Control of a Rotary Inverted Pendulum Based on LQR Mapping”, IEEE International Symposium on Intelligent Control, 2701-2706, Germany (2006).
• [5] Craig, K., Awtar, S., “Inverted Pendulum Systems: Rotary And Arm-Driven A Mechatronic System Design Case Study”, Mechatronics, 12, 357-370, 2001.
• [6] Awtar S.. et al., “Inverted pendulum Systems: rotary and arm driven – a mechatronicsystem design case”, Pergamon Pres, Mechatronics, 357-370, 2002.
• [7] Yan, Q., “Output Tracking of Underactuated Rotary Inverted Pendulum by Nonlinear Controller”, Proceedings of the 42nd IEEE Conference on Decision and Control, Maui, Hawaii, USA, December, 2003.
• [8] T. C. Kuo, Y. J. Huang, B. W. Hong, “Adaptive PID with Sliding Mode Control for the Rotary Inverted Pendulum System”, 2009 IEEE/ASME International Conference on Advanced Intelligent Mechatronics, Singapore, July 14-17, 2009.
• [9] Krishen, J., Becerra, V. M., Efficient Fuzzy Control of a Rotary Inverted Pendulum Based on LQR Mapping, Proceedings of the 2006 IEEE International Symposium on Intelligent Control Munich, Germany, October 4-6, 2006.
• [10] Khanesar, M. A., Teshnehlab, M., Shoorehdeli, M. A.,Sliding Mode Control of Rotary Inverted Pendulm, 2007 Mediterranean Conference on Control and Automation, July 27-29, 2007. Athens, Greece.
• [11] Hassanzadeh, I., Mobayen, S., PSO-Based Controller Design for Rotary Inverted Pendulum System, Journal of Applied Science 8 (16), 2907-2912, 2008.
• [12] Aydın, M., Yakut, O., ALLİ, H., Yapay Sinir Ağlı Kayan Kipli Kontrolün Dönel Ters Sarkaç Sistemine Uygulanması, Sigma Mühendislik ve Fen Bilimleri Dergisi, Sigma 5, 39-50, 2013.
• [13] Young, K.D., Utkin, V.I., Ozguner, U. A Control Engineer’s Guide to Sliding Mode Control. IEEE Transactions on Control Systems Technology 1999; 7 (3): 328-342.
• [14] Edwards C, Spurgeon S K. Sliding Mode Control: Theory and Applications. London: Taylor and Francis; 1998.